happiness dimitris ballas social and spatial inequalities (sasi) group, department of geography,...

Happiness

Dimitris BallasSocial and Spatial Inequalities (SASI) group,Department of Geography, University of Sheffieldhttp://sasi.group.shef.ac.uk/

RES-163-27-1013

ESRC Seminar Series on MicrosimulationSeminar 3: “Beyond tax-benefit modelling” School of Geography, University of Leeds, 2 July 2009

Outline• What is happiness? Can it be measured?• The socio-economic and demographic

determinants of happiness• Spatial microsimulation• Spatial microsimulation models of

happiness• Concluding comments

What is happiness? Can it be measured?

Human perceptions of happiness vary and depend on a wide range of factors

What is the good life for man? The question of what is a full and rich life cannot be answered for an individual in abstraction from the society in which he lives

(Aristotle, Nicomachean Ethics)

Can happiness be measured?Happiness is subjective and no objective theory about the

ordinary concept of happiness has the slightest plausibility (Sumner, 1996)

Can happiness be measured and modelled?

A person who has had a life of misfortune, with very little opportunities, and rather little hope, may be more easily reconciled to deprivations than others reared in more fortunate and affluent circumstances. The metric of happiness may, therefore, distort the extent of deprivation in a specific and biased way.

(Sen, 1987: 45, my emphasis)

Andrew Oswald and colleagues: statistical regression models of happiness measuring the impact of different factors and life events upon human well being

World Database of Happiness (Ruut Veenhoven)

General Health Questionnaire (1) Have you recently:

• Been able to concentrate on whatever you are doing?

• Lost much sleep over worry?• Felt that you are playing a useful part in things?• Felt capable of making decisions about things?• Felt constantly under strain?• Felt you could not overcome your difficulties?

General Health Questionnaire (2) Have you recently:

• Been able to enjoy your normal day-to-day activities?

• Been able to face up to your problems?• Been feeling unhappy or depressed?• Been losing confidence in yourself?• Been thinking of yourself as a worthless person?• Been feeling reasonably happy all things

considered?

General happiness Self Completion (4)Question Number and Text KS1L : Have you recently....been feeling reasonably happy, all things considered?

Value Label %

More so than usual 1 13.2

Same as usual 2 72.8

Less so than usual 3 11.8

Much less than usual 4 2.2

Source: The British Household Panel Survey, 1991

Factors and variables linked to subjective happiness (individual level studies)

• Age• Education• Social Class• Income• Marital status/relationships• Employment• Leisure• Religion• Health• Life events and activities

Happiness in different activities (after Layard, 2005)

Interacting with: Average happiness Friends 3.3Parents/relatives 3Spouse 2.8My children 2.7Co-workers 2.6Clients/customers etc 2.4Alone 2.2Boss 2

Can happiness be measured?

• Positive and negative feelings are inversely correlated

• Happiness can be thought of as a single variable (Layard, 2005; Frey and Stutzer, 2002)

Research questions :

• What are the factors and life events that influence different types of individuals’ happiness?

• Is the source of happiness or unhappiness purely personal or do contextual factors matter? (and if they do, to what extent?)

• Happy People or Happy Places?

Geographies of happiness in Britain

Source: The British Household Panel Survey, 1991

Region / Metropolitan Area * GHQ: general happiness Crosstabulation

% within Region / Metropolitan Area

4.5% 4.3% 14.4% 66.7% 7.7% 2.4% 100.0%

2.8% 5.7% 10.6% 68.6% 10.2% 2.1% 100.0%

2.2% 5.0% 11.9% 70.2% 9.1% 1.6% 100.0%

1.7% 3.5% 11.3% 74.1% 8.0% 1.4% 100.0%

2.1% 1.3% 10.0% 77.4% 8.5% .8% 100.0%

2.2% 1.4% 10.9% 76.0% 8.3% 1.3% 100.0%

6.6% 4.6% 11.5% 66.0% 9.9% 1.3% 100.0%

.8% 2.2% 10.7% 73.7% 10.7% 2.0% 100.0%

1.0% 2.6% 11.1% 75.2% 7.7% 2.4% 100.0%

.4% 4.7% 9.9% 75.5% 8.6% .9% 100.0%

1.3% 4.0% 14.5% 70.7% 8.1% 1.3% 100.0%

1.0% 1.7% 11.3% 71.0% 13.3% 1.7% 100.0%

2.7% 2.7% 10.7% 73.9% 8.5% 1.4% 100.0%

1.2% 5.5% 10.1% 76.5% 5.5% 1.2% 100.0%

.4% 3.8% 14.0% 72.7% 6.8% 2.3% 100.0%

1.8% 2.3% 10.8% 72.3% 11.5% 1.5% 100.0%

3.9% 1.5% 8.8% 70.9% 12.6% 2.3% 100.0%

1.8% 2.3% 10.8% 74.0% 9.9% 1.3% 100.0%

2.2% 3.4% 11.3% 72.2% 9.2% 1.6% 100.0%

Inner London

Outer London

R. of South East

South West

East Anglia

East Midlands

West MidlandsConurbation

R. of West Midlands

Greater Manchester

Merseyside

R. of North West

South Yorkshire

West Yorkshire

R. of Yorks & Humberside

Tyne & Wear

R. of North

Scotland

Region /MetropolitanArea

Missingor wild

Proxyrespondent

More thanusual

Same asusual Less so Much less

GHQ: general happiness

(%) happy more than usual

8.8 - 10.110.1 - 10.910.9 - 11.511.5 - 11.911.9 - 14.5

Spatial Microsimulation: Reweighting approaches (1)

PERSON AHID PID AAGE12 SEX AJBSTAT … AHLLT AQFVOC ATENURE AJLSEG …

1 1000209 10002251 91 2 4 … 1 1 6 9 …

2 1000381 10004491 28 1 3 … 2 0 7 -8 …

3 1000381 10004521 26 1 3 … 2 0 7 -8 …

4 1000667 10007857 58 2 2 … 2 1 7 -8 …

5 1001221 10014578 54 2 1 … 2 0 2 -8 …

6 1001221 10014608 57 1 2 … 2 1 2 -8 …

7 1001418 10016813 36 1 1 … 2 1 3 -8 …

8 1001418 10016848 32 2 -7 … 2 -7 3 -7 …

9 1001418 10016872 10 1 -8 … -8 -8 3 -8 …

10 1001507 10017933 49 2 1 … 2 0 2 -8 …

11 1001507 10017968 46 1 2 … 2 0 2 -8 …

12 1001507 10017992 12 2 -8 … -8 -8 2 -8 …

Small area table 1 (household type)

Small area table 2 (economic activity of household head)

Small area table 3 (tenure status)

Area 1 Area 1 Area 1

60 "married couple households"

80 employed/self-employed

60 owner occupier

20 "Single-person households"

10 unemployed 20 Local Authority or Housing association

20 "Other" 10 other 20 Rented privately

Area 2 Area 2 Area 2

40 "married couple households"

60 employed/self-employed

60 owner occupier

20 "Single-person households"

20 unemployed 20 Local Authority or Housing association

40 "Other" 20 other 20 Rented privately

Spatial Microsimulation: Reweighting approaches (2)

World Nation Region DistrictElectoral Wards Neighbourhood Household Individual

Levels of happiness data

World Nation Region DistrictElectoral Wards Neighbourhood Household Individual

Combining Data

1991 & 2001 Census of UK population:

100% coverage

fine geographical detail

small area data available only in tabular format with limited variables to preserve confidentiality

British Household Panel Survey:

sample size: more than 5,000 households

annual surveys since 1991

individual data

more variables than census

coarse geography

household attrition

Multilevel modelling happiness and well-being (Ballas and Tranmer, 2008)

1. “Null model” – extent of variation

2. Socio-economic variables and health – random intercepts

3. Social context – interaction variables

Ballas, D., Tranmer, M. (2008), Happy people or happy places? A multilevel modelling approach to the analysis of happiness and well-being, arXiv e-print archive, http://eprintweb.org/S/article/stat/0808.1001

Happiness and well-being determinants Model 2 Model 3 Age HLGHQ1(-),GHQL(-) HLGHQ1(-),GHQL(-) Female (Reference = Male) HLGHQ1(-),GHQL(-) HLGHQ1(-),GHQL(-) Health good (reference = health excellent) HLGHQ1(-),GHQL(-) HLGHQ1(-),GHQL(-) Health fair (reference = health excellent) HLGHQ1(-),GHQL(-) HLGHQ1(-),GHQL(-) Health poor (reference = health excellent) HLGHQ1(-),GHQL(-) HLGHQ1(-),GHQL(-) Health very poor (reference = health excellent)

HLGHQ1(-),GHQL(-) HLGHQ1(-),GHQL(-)

Employment status: unemployed (reference = employed or self employed)

HLGHQ1(-),GHQL(-) HLGHQ1(-),GHQL(-)

Employment status: family care (reference = employed or self employed)

HLGHQ1(-),GHQL(-)

Employment status: sick/disabled (reference = employed or self employed)

HLGHQ1(-),GHQL(-)

Model 2 and 3 significant main effects (1)

Happiness and well-being determinants Model 2 Model 3 Employment status: on maternity leave (reference = employed or self employed)

GHQL(+)

Employment status: on a government scheme (reference = employed or self employed)

GHQL(-)

Employment status: other job status (reference = employed or self employed)

Has lived at current address for more than 5 years (reference = lived at current address for less than one year)

HLGHQ1(+) HLGHQ1(+)

Household type: couple no children (reference = single)

HLGHQ1(+),GHQL(+) GHQL(+)

Household type: lone parent with dependent child(ren) (reference = single)

HLGHQ1(-) HLGHQ1(-)

Household type: lone parent with non dependent child(ren) (reference = single)

Household type: other (reference = single) GHQL(+) Household tenure: private renting (reference = owner occupier)

GHQL(+)

Household tenure: LA/HA renting (reference = owner occupier)

HLGHQ1(-)

Unemployment status (individual level) x unemployment rate (district level)

Not included HLGHQ1(+),GHQL(+)

Model 2 and 3 significant main effects (2)

Higher level variance components

• When the explanatory variables were added to the model, district level variation was estimated at close to, but not exactly, zero.

• Significant between-household variation remained.

Spatial Microsimulation• Reweight the first wave of the BHPS

microdata to fit small area “constraints”• Dynamically simulate this population for

the years 1991, 2001, 2011, 2021 (“groundhog day” scenario)

• What-if dynamic simulations

Ballas, D. (forthcoming), “Geographical modelling of subjective happiness and well-being”, in Stillwell, J, Norman, P., Thomas, C., Surridge, P., Understanding Population Trends and Processes, volume 2: Spatial and Social Disparities, Springer

Ballas, D. , Clarke, G.P., Dorling, D., Eyre, H. and Rossiter, D., Thomas, B. (2005)SimBritain: a spatial microsimulation approach to population dynamics. Population, Space and Place, 11, 13 – 34. doi: 10.1002/psp.351

age/sex male femaleunder-50 1 1over-50 2 1

Deterministic Reweighting the BHPS - a simple example (1)

A hypothetical sample of individuals (list format)Individual sex age-group weight1st male over-50 12nd male over-50 13d male under-50 14th female over-50 15th female under-50 1

In tabular format:

Hypothetical Census data fora small area:

Reweighting the BHPS - a simple example (2)

Calculating a new weight, so that the sample will fit into the Census table

In tabular format:

Hypothetical Census data fora small area:

Individual sex age-group weight New weight 1st male over-50 1 1 x 3/2 = 1.5 2nd male over-50 1 1 x 3/2 = 1.5 3d male under-50 1 1 x 3/1 = 3 4th female over-50 1 1 x 1/1 = 1 5th female under-50 1 1x 5/1 = 5

Modelling approach

1. Establish a set of constraints2. Choose a spatially defined source population3. Repeatedly sample from source4. Adjust weightings to match first constraint5. Adjust weightings to match second constraint6. …7. Adjust weightings to match final constraint8. Go back to step 4 and repeat loop until results

converge9. Save weightings which define membership of

SimBritain

MODEL CONSTRAINTS

• 1971, 1981 and 1991 Census Small Area Statistics (SAS)

• 6 constraint tables with 3 categories• projected forward for 2001, 2011 and 2021• ward level projections

CONSTRAINT TABLES

TABLE CATEGORY

Car Ownership no cars 1 car 2+ cars

Social Class affluent middle income less affluent

Demography 1 child 2+ children no children

Employment active retired inactive

Households married couple lone parent other

Tenure owner occupied council tenant other

Simulated geography of happiness in Scotland (%) happy more than usual, 1991

parliamentary constituencies9.971 - 10.31610.316 - 10.60710.607 - 10.96810.968 - 11.34811.348 - 11.987

Estimated geography of happiness in Wales (%) happy more than usual, 1991

Welsh Unitary Authorities (%)8.918.91 - 9.479.47 - 10.0110.01 - 10.3710.37 - 10.65

Welsh Unitary Authorities (%)10.61 - 11.0511.05 - 11.6811.68 - 12.2812.28 - 13.7513.75 - 14.54

Estimated geography of happiness in London (%) happy more than usual, 1991

Parliamentary constituencies10.15 - 11.2411.24 - 12.2512.25 - 12.8312.83 - 13.5513.55 - 15.95

(%) “affluent households”, 1991

(%) “average” households, 1991

(%) “poor” households, 1991

(%) much less happy than usual, 1991

Concluding comments• Some district level variation in happiness – but the

differences from place to place (at district level) do not appear to be statistically significant.

• Spatial microsimulation can be used to disaggregate geographically the analysis further

• But the reliability of the results may be significantly affected by the small area constraints and “Place/individual variable interactions”

• On-going work: - further refinement of the static models/simulated

annealing- Longitudinal analysis- Environmental variables

On-going and future work

• Public Policy Analysis and Happiness• Modelling the environmental

determinants of happiness• International happiness comparisons• Subjective Happiness and Human-

Scale Visualisations

Combining spatial microsimulation model outputs with remote sensing

Spatial microsimulation output:

• No. of residents in household (as a proxy to house size)

• House type• Number of cars (as a

proxy to house size)• Number of rooms in

household space (as a proxy to house size)

Remotely sensed data:

• land use• property size• house type

“visibility” data

The view from here

Life-events and happiness

• BHPS: What has happened to you (or your family) which has stood out as important?

• 145,408 major life events recorded between 1992-1995

Ballas, D., Dorling, D. (2007) Measuring the impact of major life events upon happiness, International Journal of Epidemiology, 36, 1244-1252. doi:10.1093/ije/dym182

Life Event Coefficient P value

RELATIONSHIPS (MINE ENDING 36,43) -0.178 0.00

DEATH (PARENT, 45) -0.166 0.00

HEALTHPARENT (1-9) -0.139 0.00

DEATH (OTHER 45) -0.137 0.00

EMPLOYMENT JOB LOSS 24 -0.129 0.00

HEALTH MINE (1-9) -0.117 0.00

DEATH (FAMILY 45) -0.098 0.00

HEALTH PARTNER (1-9) -0.092 0.00

HEALTH CHILD (1-9) -0.084 0.00

HEALTH OTHER (1-9) -0.073 0.00

EDUCATION CHILD (12-19) -0.029 0.12

EMPLOYMENT OTHER (23,26-29) -0.028 0.13

OTHER EVENT (10-11;32-34;37-39;90-95) -0.026 0.14

NOTHING IMPORTANT HAPPENED -0.022 0.11

RELATIONSHIPS (WITH PET 54 AND SUBJECT) -0.020 0.44

FINANCE (OTHER 60-69;73-79) -0.019 0.27

RELATIONSHIPS FAMILY (46-53;55-59) -0.014 0.39

Life Event Coefficient P value

RELATIONSHIPS (FAMILY 35. 41-42) 0.002 0.91

LEISURE (OUR HOLIDAY 30) 0.010 0.61

MOVING HOME (44;80-81) 0.013 0.46

EDUCATION OTHER (12-19) 0.024 0.27

FINANCE (CAR 70) 0.027 0.22

LEISURE (MY HOLIDAY 30) 0.029 0.07

PREGNANCY (OTHER 40) 0.031 0.56

PREGNANCY (FAMILY 40) 0.034 0.09

RELATIONSHIPS (CHILD'S STARTING 35, 42) 0.037 0.10

EMPLOYMENT JOB CHANGE (20-21) 0.040 0.02

LEISURE (OTHER 30-31) 0.043 0.02

EDUCATION MINE(12-19) 0.052 0.00

PREGNANCY (CHILD'S 40) 0.053 0.01

PREGNANCY (MINE 40) 0.084 0.00

FINANCE (HOUSE 71) 0.097 0.00

EMPLOYMENT JOB GAIN 22 0.097 0.00

RELATIONSHIPS (MINE STARTING 35. 42) 0.160 0.00

6.0%5.0%4.0%3.0%2.0%1.0%0.0%

Percent

Finance etc

Relationships

Births and Deaths

Leisure

Employment

Education

HealthEvent theme

Acknowledgements

• Funding from the Economic and Social Research Council (RES-163-27-1013) is gratefully acknowledged.

• The British Household Panel Survey data were made available through the UK Data Archive. The data were originally collected by the ESRC Research Centre on Micro-social Change at the University of Essex, now incorporated within the Institute for Social and Economic Research.

• The Census Small-area Statistics used in some of the work presented here are Crown Copyright and are provided through the Census Dissemination Unit of the University of Manchester, with the support of the ESRC/JISC/DENI 1991 Census of Population Programme.

happiness dimitris ballas social and spatial inequalities (sasi) group, department of geography,...

source of happiness

correlated happiness

metric of happiness

human perceptions of

ordinary concept of

comments slide

good life

life of misfortune

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